In the conditions prevalent on earth, chemical reactions mediate much of the physical change, most of the energy-transduction processes, and all known biology. Although the quantum mechanical equations needed to predict the properties of these ubiquitous chemical reactions have been known for more than fifty years, their computational intractability prohibited the widespread application of ab initio (from first principles) chemical modeling to real-world problems. With the advent of vector and parallel supercomputers, ab initio quantum chemistry became feasible for molecules containing up to dozens of atoms and has since had a dramatic impact on chemistry, biochemistry, and materials science. Nevertheless, before quantum chemistry can fulfill its ultimate promise as a true "virtual chemistry laboratory", many advances must be made. In order to use the vast range of modern computing hardware, from workstations to massively parallel computers, we have written an ab initio quantum chemistry program that runs efficiently on both serial processors and shared- and distributed-memory parallel computers. A unique aspect of this program (at least among quantum chemistry software) is that it is written entirely in C++, using the object-oriented mechanism of "abstraction" to isolate the architecture dependent code. This program currently includes the two most common ab initio quantum chemical methods, Hartree-Fock and second order Moller Plesset Perturbation theory, and is being extended to include density functional theory and polarizable continuum solvation models. We are using this software on Sandia's massively parallel computers to study several real- world projects in biochemistry, including joint theoretical/experimental collaborations on anticancer drugs, environmental carcinogens, and modified DNA oligomers. These projects involved performing some of the largest ab initio quantum chemical calculations ever done. In this talk I will describe the role of computational chemistry in these biochemical applications. Also, I will discuss our experiences with using C++ for parallel scientific programming and our ongoing software development efforts.